The steps by which neutral, random and/or negative biological interactions evolve into mutualistic ones remain poorly understood. Here, we study Elacatinus gobies and the fishes from which they clean parasites, termed 'clients'. Colorful stripes are common to mutualist cleaners and non-cleaning sister species. Blue stripes are unique to obligate cleaners. We quantified the contrast potential of ancestral and novel stripe colors, using fish color vision models, and determined that color stripes have become more visible to clients over evolutionary time. In turn, we focused on the role of color as a potentially specialized signal. We show that cleaners possess a putative chemical defense (one multimedia file in .mov format included) and demonstrate that stripes are sufficient to elicit client stereotypical posing behavior and to deter attack. Analysis of previously published records show that yellow cleaners tend to predators less than expected, compared to green and blue cleaners. Our results highlight evolution from predator avoidance to tolerance with conspicuous advertising reinforced by chemical defense in cleaners. Similar trajectories, via recognizable signals to risky partners, may be common in other diffuse mutualisms. We discuss the generality of defense and signal traits in other species rich lineages of mutualists.

Ce rapport d'HDR présente les résultats de 10 ans de travaux basés sur l'utilisation de microcosmes lentiques de laboratoire en écotoxicologie aquatique et propose une analyse critique de cette approche en faisant ressortir ses avantages par rapport aux tests monospécifiques mais aussi ses limites (variabilité notamment)

Due to several reasons, treatment methods for a certain waste are oftennot available locally in the waste handling and management industry. This is especially true for regions which are not densely populated. This requires transports, the majority of which consumes fossil fuel. To avoid this, local waste treatment methods need to be developed. In this work it is investigated how treatment of one hazardous waste is done; water and sludge containing oil. Based on sustainability criteria three novel methods are presented that can be conducted locally; mycoremediation, phytoremediation and electrocoagulation. The methods are evaluated in a case study of a recycling company. Mycoremediation and electrocoagulation were found to be suitable in the case study, as long as some criteria are fulfilled. In addition it is shown what barriers exist in law, policies and practices that hinder local treatment of water and sludge containing oil.

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Symbiosis is one of the most widespread evolutionary strategies on Earth. In the deep-sea, symbioses between chemosynthetic bacteria and invertebrates are abundant at hydrothermal vents and cold seeps. These mutualisms, in which symbiont carbon fixation provides for host nutrition, are analogous to the ancient endosymbioses that resulted in the chloroplast and the eukaryotic mitochondrion. However, the evolutionary processes that led to the widespread dispersal of deep-sea organisms and the mechanisms by which symbioses are initiated and maintained are poorly characterized. This thesis examined the evolution of deep-sea mussels (Bathymodiolinae) and their chemosynthetic symbionts. Bathymodioline mussel taxonomy is in need of a comprehensive systematic revision because the majority of named genera do not constitute monophyletic groups. First, this thesis demonstrated that mussels found on the Northeast Pacific Ridges are members of Adipicola, a paraphyletic genus within Bathymodiolinae, refining the evolutionary history of this poorly characterized group. Second, an updated multi-locus phylogeny of bathymodiolines was presented and used to evaluate the statistical evidence for previously proposed hypotheses describing the directional evolution of bathymodioline traits. The results indicated that patterns of directional evolution in this group are not well supported and instead suggests that trait evolution has proceeded in a non-directional manner. Third, this thesis presented the first evidence of detection and abundance of bathymodioline symbionts in the deep-sea environment, providing direct evidence that these symbionts are environmentally acquired. Fourth, this thesis presented the first multi-locus phylogenies of bathymodioline symbionts and tested the hypothesis of environmental acquisition of symbionts in this group. The results demonstrated that symbiont and host lineages are decoupled, which is consistent with the environmental acquisition hypothesis. Finally, environmental acquisition implies that symbionts have opportunities to exchange genetic information with other bacterial strains and evidence for recombination in bathymodioline symbionts is also presented. This thesis advances our understanding of the evolutionary history of bathymodioline symbioses by clarifying host and symbiont evolutionary history and symbiont transmission strategy. In aggregate, these results suggest that bathymodiolines are more flexible with regard to the habitats they inhabit and the symbionts they harbor than previously understood.

Many insects form symbioses with maternally inherited, intracellular bacteria, which can have major effects on the ecology and evolution of the insect host. Here I investigated the interaction between a global agricultural pest, Bemisia tabaci (the sweetpotato whitefly), and a Rickettsia bacterial symbiont. Rickettsia had previously been tracked sweeping through field populations of B. tabaci in the southwestern USA and had been shown to dramatically increase whitefly fitness under laboratory conditions. In contrast, the Rickettsia present in whiteflies in Israel has few observable fitness effects and is declining in frequency in field populations. I explored the population dynamics of Rickettsia in B. tabaci field populations in the USA and Israel, and assessed the genetic diversity of the Rickettsia in these populations. In laboratory experiments, there was no observable effect of Rickettsia on the heat shock or constant temperature tolerance of USA B. tabaci. Instead, whitefly genetic background appears to influence the effects of Rickettsia. Lastly, analysis of the genome sequence of Rickettsia provided insights into the mechanism of the fitness benefit and evolutionary history of the bacterium. Taken together, these integrated ecological, physiological and genomic studies provide some explanation for the contrasting and wide-ranging phenotypes associated with whitefly Rickettsia, and provide support for the hypothesis that the fitness benefit provided by Rickettsia is context dependent. The Rickettsia symbiosis exhibits geographically distinct population dynamics, is affected by whitefly genotype, and may involve manipulation of host plants and/or defense against pathogens rather than nutritional supplementation. Overall, these results highlight the important role that microbial symbionts may play in the adaptation of invasive species to changing environments.

Plant microbiomes are increasingly appreciated as major drivers of plant health and ecosystem services, and are of ever-greater interest for their potential in human applications. However, plant-associated microorganisms often live in complex associations in nature. Here, I characterize one of these microbial associations: the symbiosis between foliar fungal endophytes and their bacterial endosymbionts (endohyphal bacteria, EHB). EHB influence fungal phenotypes and can shape the outcomes of plant-fungal interactions. EHB are thought to form facultative associations with many foliar fungi in the species-rich Ascomycota, but little is known about how these symbioses are initiated and maintained, or how EHB shape the ecology of their fungal hosts. In this study, I assessed factors mediating the relationships between two foliar fungi (Microdiplodia sp., Dothideomycetes; Pestalotiopsis sp. Sordariomycetes) and their EHB. I first established methods for introducing EHB into axenic mycelia of their fungal hosts, providing an important step forward for understanding the establishment of EHB associations and a critical tool for experimental tests of the effects of EHB on fungal phenotypes. Through experiments in vitro, I found that both the identity of the fungal host and the conditions under which fungi and bacteria are grown influence the establishment of EHB/fungal associations. Moreover, I showed EHB of foliar fungi can be transferred across fungal classes, thus creating experimental strains that could be used for the first time to examine the contribution of each symbiont to important fungal traits. Using these strains I evaluated how EHB influence the capacity of foliar fungi to degrade plant material as saprotrophs. I found that the presence and identity of EHB significantly influenced fungal growth on particular media, cellulase and ligninase activity, and mass loss from senescent tissue of their native host plant species in a partnership-specific manner. Because EHB can be acquired horizontally, they may help shape plant-fungal interactions, resultant ecosystem services, and the functional diversification of plant-associated fungi along the saprotroph-endophyte continuum. By manipulating EHB/fungal interactions in new ways, we can potentially influence fungal phenotypes for diverse human applications.

This thesis investigates the use of symbiosis as an evolutionary metaphor for problem decomposition using Genetic Programming. It begins by drawing a connection between lateral problem decomposition, in which peers with similar capabilities coordinate their actions, and vertical problem decomposition, whereby solution subcomponents are organized into increasingly complex units of organization. Furthermore, the two types of problem decomposition are associated respectively with context learning and layered learning. The thesis then proposes the Symbiotic Bid-Based framework modeled after a three-staged process of symbiosis abstracted from biological evolution. As such, it is argued, the approach has the capacity for both types of problem decomposition. Three principles capture the essence of the proposed framework. First, a bid-based approach to context learning is used to separate the issues of `what to do' and `when to do it'. Whereas the former issue refers to the problem-specific actions, e.g., class label predictions, the latter refers to a bidding behaviour that identifies a set of problem conditions. In this work, Genetic Programming is used to evolve the bids casting the method in a non-traditional role as programs no longer represent complete solutions. Second, the proposed framework relies on symbiosis as the primary mechanism of inheritance driving evolution, where this is in contrast to the crossover operator often encountered in Evolutionary Computation. Under this evolutionary metaphor, a set of symbionts, each representing a solution subcomponent in terms of a bid-action pair, is compartmentalized inside a host. Communication between symbionts is realized through their collective bidding behaviour, thus, their cooperation is directly supported by the bid-based approach to context learning. Third, assuming that challenging tasks where problem decomposition is likely to play a key role will often involve large state spaces, the proposed framework includes a dynamic evaluation function that explicitly models the interaction between candidate solutions and training cases. As such, the computational overhead incurred during training under the proposed framework does not depend on the size of the problem state space. An approach to model building, the Symbiotic Bid-Based framework is first evaluated on a set of real-world classification problems which include problems with multi-class labels, unbalanced distributions, and large attribute counts. The evaluation includes a comparison against Support Vector Machines and AdaBoost. Under temporal sequence learning, the proposed framework is evaluated on the truck reversal and Rubik's Cube tasks, and in the former case, it is compared with the Neuroevolution of Augmenting Topologies algorithm. Under both problems, it is demonstrated that the increased capacity for problem decomposition under the proposed approach results in improved performance, with solutions employing vertical problem decomposition under temporal sequence learning proving to be especially effective.

This research investigates the ability of genetic programming to build profitable trad- ing strategies for the Foreign Exchange Market (FX) of one major currency pair (EURUSD) using one hour prices from July 1, 2009 to November 30, 2012. We rec- ognize that such environments are likely to be non-stationary and we do not expect that a single training partition, used to train a trading agent, represents all likely future behaviours. The proposed adaptive retraining algorithm – hereafter FXGP – detects poor trading behaviours and trains a new trading agent. This represents a significant departure from current practice which assumes some form of continuous evolution. Extensive benchmarking is performed against the widely used EURUSD currency pair. The non-stationary nature of the task is shown to result in a prefer- ence for exploration over exploitation. Moreover, adopting a behavioural approach to detecting retraining events is more effective than assuming incremental adaptation on a continuous basis. From the application perspective, we demonstrate that use of a validation partition and Stop-Loss (S/L) orders significantly improves the perfor- mance of a trading agent. In addition the task of co-evolving of technical indicators (TI) and the decision trees (DT) for deploying trading agent is explicitly addressed. The results of 27 experiments of 100 simulations each demonstrate that FXGP sig- nificantly outperforms existing approaches and generates profitable solutions with a high probability.

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